6G Radio-Based Parking Lot Detection

The sixth-generation (6G) of mobile networks is envisioned to join the state of the physical world with the digital world by enabling sensing abilities at the communication device. In this paper we investigate the task of radio-based parking lot detection using a (potential) 6G base station setting. Exploiting the workhorse of communication, namely orthogonal frequency division multiplex (OFDM), we formalize the Radio Detection And Ranging (RADAR) task. Further, the challenge of projection from a single base station, creating overlapping parking-lots in range and angle, is demonstrated. Leveraging a ray-tracing framework allowing to randomize different realistic parking scenarios, a state-of-the art Neural Network (NN) is optimized and rigorously investigated using classification metrics. Different hardware configurations and occupancy levels are investigated, concluding, that radio-based parking lot detection will be a viable task for 6G communication devices.